Comparing Quality Levels between Machines, Parts or Shifts

Kyle Cahoon
By Kyle Cahoon | August 6, 2012
Application Engineer

Continuous process improvement does not always seem like a realistic task during what already feels like overly busy days. Work days (and nights) are spent conforming to customer compliance standards, investigating customer complaints or struggling with data collection hardware and software.

Tasks pile up, demands increases and products become more diverse - it may seem like the demands on your time will always outpace your ability to fulfill them. How do you find ways to create real value?

The first step is to look closely at how you are collecting data. Typically, quality data is sampled during the process to determine if the product (part) is in compliance. These data are often appended to traceability information such as a lot, purchase order number, work order number, etc. This is the bare minimum for satisfying customer needs and to be able to respond to a recall. Let’s look at adding machine, part, and shift to increase your data’s resolution and make it more valuable.


There are one or more machines ultimately responsible for certain quality criteria measured on a given part. Capturing the machine as an identifier such as asset number rather than simply "Line 1" gives you increased resolution of the process. If machines are switched out, upgraded, or replaced you can focus on the process performance of each one individually. This enables you to provide a more accurate benchmark of your process. Remember, the process can be defined how you see fit and adding resolution to your data collection gives you more options.


You are probably collecting a "part" with your quality data but you may want to consider adding more detail. For example, assign a work in progress (WIP) part number at different stages of production. This will enable comparative analysis at multiple levels giving you greater resolution for recalls. It will also allow you to pinpoint, not only under-performing products, but specific problem areas within your process with more certainty.


There is always a human component to your process performance. Appending shift to quality data is not the same as simply noting the time that check was performed. Adding a shift indicator to your data will allow you to aggregate data by shift, regardless of the specific date/time the data were collected. Try looking at the CPK of a given process/part/test combination. Now look at the same data but by individual shift. What if Third Shift performance yields a CPK of 0.87 while First Shift yields 1.34? This could help you quickly identify issues such as understaffing or inadequate training.

Process improvement is all about collecting the right data so that you can see your process, not only at a high level, but with high resolution. Comparative analysis of quality data by machine, part and shift can quickly identify areas to improve on rather than tackling too many variables at once. It’s time to start making your quality data truly valuable.

InfinityQS Fact Checking Standards

InfinityQS is committed to delivering content that adheres to the highest editorial standards for objective analysis, accuracy, and sourcing.

  • We have a zero-tolerance policy regarding any level of plagiarism or malicious intent from our writers and contributors.
  • All referenced articles, research, and studies must be from reputable publications, relevant organizations, or government agencies.
  • Where possible, studies, quotes, and statistics used in a blog article contain a reference to the original source. The article must also clearly indicate why any statistics presented are relevant.
  • We confirm the accuracy of all original insights, whether our opinion, a source’s comment, or a third-party source so as not to perpetuate myth or false statements.



Never miss a post. Sign up to receive a weekly roundup of the latest Quality Check blogs.